Required packages
Variables used:
prepare the dataset for modeling
## [1] "radiation" "nightlight_450" "nightlight_4950"
## [4] "nightlight_3150" "nightlight_900" "elevation"
## [7] "industry_1000" "industry_100" "industry_25"
## [10] "industry_3000" "industry_300" "industry_5000"
## [13] "industry_500" "industry_50" "population_1000"
## [16] "population_3000" "population_5000" "road_class_1_1000"
## [19] "road_class_1_100" "road_class_1_25" "road_class_1_3000"
## [22] "road_class_1_300" "road_class_1_5000" "road_class_1_500"
## [25] "road_class_1_50" "road_class_2_1000" "road_class_2_100"
## [28] "road_class_2_25" "road_class_2_3000" "road_class_2_300"
## [31] "road_class_2_5000" "road_class_2_500" "road_class_2_50"
## [34] "road_class_3_1000" "road_class_3_100" "road_class_3_25"
## [37] "road_class_3_3000" "road_class_3_300" "road_class_3_5000"
## [40] "road_class_3_500" "road_class_3_50" "temperature_2m_10"
## [43] "temperature_2m_11" "temperature_2m_12" "temperature_2m_1"
## [46] "temperature_2m_2" "temperature_2m_3" "temperature_2m_4"
## [49] "temperature_2m_5" "temperature_2m_6" "temperature_2m_7"
## [52] "temperature_2m_8" "temperature_2m_9" "trop_mean_filt"
## [55] "wind_speed_10m_10" "wind_speed_10m_11" "wind_speed_10m_12"
## [58] "wind_speed_10m_1" "wind_speed_10m_2" "wind_speed_10m_3"
## [61] "wind_speed_10m_4" "wind_speed_10m_5" "wind_speed_10m_6"
## [64] "wind_speed_10m_7" "wind_speed_10m_8" "wind_speed_10m_9"
## [67] "mean_value"
## [1] "radiation" "nightlight_450" "nightlight_4950"
## [4] "nightlight_3150" "nightlight_900" "elevation"
## [7] "industry_1000" "industry_100" "industry_3000"
## [10] "industry_300" "industry_5000" "industry_500"
## [13] "population_1000" "population_3000" "population_5000"
## [16] "road_class_1_1000" "road_class_1_100" "road_class_1_3000"
## [19] "road_class_1_300" "road_class_1_5000" "road_class_1_500"
## [22] "road_class_2_1000" "road_class_2_100" "road_class_2_3000"
## [25] "road_class_2_300" "road_class_2_5000" "road_class_2_500"
## [28] "road_class_3_1000" "road_class_3_100" "road_class_3_3000"
## [31] "road_class_3_300" "road_class_3_5000" "road_class_3_500"
## [34] "temperature_2m_10" "temperature_2m_11" "temperature_2m_12"
## [37] "temperature_2m_1" "temperature_2m_2" "temperature_2m_3"
## [40] "temperature_2m_4" "temperature_2m_5" "temperature_2m_6"
## [43] "temperature_2m_7" "temperature_2m_8" "temperature_2m_9"
## [46] "trop_mean_filt" "wind_speed_10m_10" "wind_speed_10m_11"
## [49] "wind_speed_10m_12" "wind_speed_10m_1" "wind_speed_10m_2"
## [52] "wind_speed_10m_3" "wind_speed_10m_4" "wind_speed_10m_5"
## [55] "wind_speed_10m_6" "wind_speed_10m_7" "wind_speed_10m_8"
## [58] "wind_speed_10m_9" "mean_value"
##
## % Table created by stargazer v.5.2.2 by Marek Hlavac, Harvard University. E-mail: hlavac at fas.harvard.edu
## % Date and time: Thu, Sep 10, 2020 - 13:34:13
## \begin{table}[!htbp] \centering
## \caption{}
## \label{}
## \begin{tabular}{@{\extracolsep{5pt}} ccc}
## \\[-1.8ex]\hline
## \hline \\[-1.8ex]
## & Var1 & Freq \\
## \hline \\[-1.8ex]
## 1 & nightlight\_450 & $20$ \\
## 2 & population\_1000 & $20$ \\
## 3 & population\_3000 & $20$ \\
## 4 & road\_class\_1\_5000 & $20$ \\
## 5 & road\_class\_2\_100 & $20$ \\
## 6 & road\_class\_3\_300 & $20$ \\
## 7 & trop\_mean\_filt & $20$ \\
## 8 & road\_class\_3\_3000 & $19$ \\
## 9 & road\_class\_1\_100 & $18$ \\
## 10 & road\_class\_3\_100 & $14$ \\
## 11 & road\_class\_3\_5000 & $6$ \\
## 12 & road\_class\_1\_300 & $5$ \\
## 13 & road\_class\_1\_500 & $5$ \\
## 14 & road\_class\_2\_1000 & $2$ \\
## 15 & nightlight\_3150 & $1$ \\
## 16 & road\_class\_2\_300 & $1$ \\
## 17 & road\_class\_3\_1000 & $1$ \\
## 18 & temperature\_2m\_7 & $1$ \\
## \hline \\[-1.8ex]
## \end{tabular}
## \end{table}
Variable importance: 20-times bootstrapping
##
## % Table created by stargazer v.5.2.2 by Marek Hlavac, Harvard University. E-mail: hlavac at fas.harvard.edu
## % Date and time: Thu, Sep 10, 2020 - 13:36:34
## \begin{table}[!htbp] \centering
## \caption{}
## \label{}
## \begin{tabular}{@{\extracolsep{5pt}} ccc}
## \\[-1.8ex]\hline
## \hline \\[-1.8ex]
## rank & xgboost & randomforest \\
## \hline \\[-1.8ex]
## 1 & population\_3000 & population\_3000 \\
## 2 & road\_class\_3\_3000 & road\_class\_2\_100 \\
## 3 & population\_1000 & road\_class\_3\_3000 \\
## 4 & nightlight\_450 & population\_1000 \\
## 5 & road\_class\_2\_100 & nightlight\_450 \\
## 6 & road\_class\_3\_300 & nightlight\_3150 \\
## 7 & road\_class\_1\_5000 & population\_5000 \\
## 8 & nightlight\_3150 & road\_class\_3\_300 \\
## 9 & road\_class\_3\_100 & nightlight\_900 \\
## 10 & population\_5000 & road\_class\_3\_5000 \\
## 11 & trop\_mean\_filt & road\_class\_2\_300 \\
## 12 & radiation & road\_class\_3\_100 \\
## 13 & nightlight\_900 & nightlight\_4950 \\
## 14 & road\_class\_3\_5000 & trop\_mean\_filt \\
## 15 & road\_class\_1\_100 & road\_class\_1\_5000 \\
## 16 & nightlight\_4950 & industry\_5000 \\
## 17 & temperature\_2m\_2 & road\_class\_1\_3000 \\
## 18 & road\_class\_1\_3000 & temperature\_2m\_2 \\
## 19 & elevation & road\_class\_2\_500 \\
## 20 & industry\_5000 & elevation \\
## \hline \\[-1.8ex]
## \end{tabular}
## \end{table}
## [1] 0.1901088
## [1] 1.222033
## [1] 0.1556689
## [1] 1.205287
## [1] 0.1268883
## [1] 1.183365
## [1] 0.3882069
## [1] 1.427972
## [1] 0.04430768
## [1] 1.149795
## [1] 0.1826481
## [1] 1.552059
## [1] 0.1971566
## [1] 1.267337
## [1] 0.3548291
## [1] 1.305196
## [1] 0.08162944
## [1] 1.212171
## [1] 0.145498
## [1] 1.356919
## [1] 0.05589182
## [1] 1.321556
## [1] 0.1392856
## [1] 1.183584
## [1] 0.2408565
## [1] 1.285379
## [1] 0.2511692
## [1] 1.221336
## [1] 0.03772771
## [1] 1.294238
## [1] 0.2006586
## [1] 1.175262
## [1] 0.08578486
## [1] 1.398079
## [1] 0.08656745
## [1] 1.410834
## [1] 0.09301482
## [1] 0.9520355
## [1] 0.2299919
## [1] 1.019007